Entries Tagged ‘HIL’

While working on some complex control systems for aerospace projects, I had the opportunity to build and use hardware-in-the-loop (HIL or HWIL) simulations. A HIL simulation is a platform where you can swap different portions of the system between simulation models and real hardware. The ability to mix simulated and real components provides a mechanism to test and characterize the behavior and interactions between components. This is especially valuable when building closed-loop control systems that will perform in conditions that you do not fully understand yet (due to a lack of experience with the operating scenario).

Building a HIL simulation is an extensive effort. The simulation must be able to not only emulate electrical signals for sensors and actuators, but it may also need to be able to provide predictable and repeatable physical conditions, such as moving the system around on six degrees of freedom based on real or simulated sensor or actuator outputs. As a result, HIL can be cost prohibitive for many projects; in fact, to date the only people I have met that have used HIL worked on aircraft, spacecraft, automotive, and high-end networking equipment.

I suspect though with the introduction of more sensors and/or actuators in consumer level products, that HIL concepts are being used in new types of projects. For example, tablet devices and smartphones increasingly are aware of gravity. To date, being able to detect gravity is being used to set the orientation on the display, but I have seen lab work where these same sensors are being used to detect deliberate motions made by the user, such as shaking, lowering, or raising the device. At that point, HIL concepts provide a mechanism for developers to isolate and examine reality versus their assumptions about how sets of sensors and/or actuators interact under the variation that can occur under each of these use scenarios.

In my own experience, I have used HIL simulation to characterize and understand how to successfully use small rocket engines to move and hover a vehicle in the air. The HIL simulation allowed us to switch between real and simulated engines that moved the system. This kind of visibility was especially useful because operating the vehicle was dangerous and expensive. Another HIL simulation allowed us to work with the real camera sensor and physically simulate the motion that the camera would experience in a usage scenario. In each of these simulation setups, we were able to discover important discrepancies between our simulation models and how the real world behaved.

Are HIL simulation concepts moving into “simpler” designs? Are you using HIL simulation in your own projects? Is it sufficient to work with only real hardware, say in the case of a smartphone, or are you finding additional value in being able to simulate specific portions of the system on demand? Are you using HIL in a different way than described here? Is HIL too esoteric a topic for most development?